The phenomenon of population aging in rural China presents a compelling societal challenge, necessitating a growing demand for both the quantity and quality of facilities supporting the needs of older people. However, a lack of comprehensive understanding concerning the underlying mechanisms that drive the emergence of these facilities, coupled with the distinctive historical backdrop and social development stage of the nation, engenders complexities in achieving sustainable rural eldercare services. This paper endeavors to comprehensively elucidate diverse eldercare facility types in rural China, delineating their intrinsic characteristics and prerequisites for construction. Additionally, the research delves into the political and economic contexts and advancements in healthcare and eldercare services, culminating in the formulation of an integrated framework that interconnects eldercare support patterns with the political landscape and public service provisions. The implications derived from this nuanced framework provide insightful reflections on significant historical transitions, intricacies faced by rural eldercare facilities, and strategic pathways for fostering future eldercare service delivery systems and allied facilities. The paper’s findings furnish insights for bolstering the well-being of the aging population in rural China and lay a substantive foundation for addressing the evolving requisites of eldercare within this distinctive context.

Severe aging in rural China is prompting communities to promote support for older people to age in place. The study of the daily life of older adults in rural areas is conducive to understanding their real life and demands, as well as the way they interact with their environment, to develop feasible strategies. In this study, 171 older adults over 60 years old in two different types of villages in Northern Zhejiang Province were investigated and analyzed in terms of the temporal and spatial features of daily activities, as well as their relationship with population attributes, personal competence, and subjective demands. The results show that: (1) significant association can be seen between working hours and the demand for health services, housework hours and gender and age, as well as leisure hours and ADL and the demand for recreational services. (2) The older adults appear to have inter-group homogeneity in some aspects: basic living activities, leisure hours, the gender difference in housework hours, and recreational preference, while they have higher average paid work hours and fewer leisure alternatives than their urban counterparts. Their definitions of paid work, housework, and leisure activities are vague. (3) The definition of home by the older adults in rural places sometimes seems to go beyond the scope of their own house, and the extensive definition of home may change their recognitions of some activities. They also inclined to assign meaning to a place through frequent use rather than through external definitions. (4) The weak consciousness on buying services and deteriorated financial situation hinders the older adults in rural communities from expressing their real demands. Unspoken demands include economic security, recreational choices, and assistance in housework. The results will help to provide references for the improvement of eldercare services and the community environment.

The construction of community elderly care facilities (CECF) is pivotal for promoting healthy aging and “aging in place” for older people. This study focuses on the low utilization rates of community elderly care facilities in the Dongcheng and Xicheng Districts, core areas of Beijing. The explainable machine learning method is used to analyze data across three dimensions: the elderly’s individual attributes, characteristics of the community elderly care station (CECS), and features of the built environment around CECS and subdistrict, to identify the important factors that influence the usage frequency of overall CECS and its different functional spaces, and also the correlation between factors and usage frequency of CECS. It shows that the most important factors are the features of CSCF, including the degree of space acceptance and satisfaction with services provided, which influence the usage frequency of nine functional spaces (R² ≥ 0.68) and overall (R² = 0.56). In addition, older people’s individual factors, such as age and physical condition, significantly influence the usage of specific spaces such as rehabilitation therapy rooms and assistive bathing rooms. The influence of built environment characteristics is relatively low, with factors such as the density of bus stations and housing prices within the subdistrict and the mean distance from CECF to the nearest subway stations being more important. These findings provide a reference for the construction of indoor environments, management of service quality, and optimal site selection for future community elderly care facilities.